Triple
T13052850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabot |
E327489
|
entity |
| Predicate | hasVariantForm |
P457
|
FINISHED |
| Object | Caboto |
E10769
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Caboto | Statement: [Cabot, hasVariantForm, Caboto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caboto Context triple: [Cabot, hasVariantForm, Caboto]
-
A.
John Cabot
chosen
John Cabot was an Italian-born navigator and explorer, sailing under the English flag, best known for his late 15th-century voyages to North America that helped lay the groundwork for England’s claims in the New World.
-
B.
Martin Frobisher
Martin Frobisher was a 16th-century English seafarer and privateer best known for his early Arctic voyages in search of a Northwest Passage to Asia.
-
C.
Arthur Frobisher
Arthur Frobisher is a wealthy, corrupt corporate executive and primary antagonist in the legal thriller TV series "Damages."
-
D.
Alexandre Cabot
Alexandre Cabot is an individual notable enough to be recognized as a prominent bearer of the Cabot surname.
-
E.
John Moors Cabot
John Moors Cabot was an American diplomat and philanthropist from the prominent Cabot family, known for his service as a U.S. ambassador and benefactor to cultural and educational institutions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980b98fa081908cfa92116799e874 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ead25b7c8190af2ccf26b44c2ea2 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 8:58 p.m.